Nodal, zonal, or uniform electricity pricing： how to deal withnetwork congestion

In this paper, the main contributions to congestion management and electricity pricing, i.e., nodal, zonal, and uniform electricity pricing, are surveyed. The key electricity market concepts are structured and a formal model framework is proposed for electricity transportation, production, and consumption in the context of limited transmission networks and competitive, welfare maximizing electricity markets. In addition, the main results of existing short-run and long-run congestion management studies are explicitly summarized. In particular, the important interconnection between short-run network management approaches and optimal long-run investments in both generation facilities and network lines are highlighted.

Medium-term scheduling of operating states in electric power systems

This article presents a mathematical model for the medium-term scheduling of the operating states of electric power systems.The scheduling period is divided into several time intervals.The model can be used to determine the equilibrium state in which each supplier earns maximum profit from supplying electricity to the wholesale market.We estimated the maximum value of public welfare,which indicates the total financial gains of suppliers and consumers,to determine the prices at the nodes of the power system.This was done by considering the balance constraints at the nodes of the power system and constraints on the allowable values of generation,power flows,and volumes of energy resources consumed over several time intervals.This problem belongs to the class of bi-level Stackelberg game-theoretic models with several leaders.The market equilibrium is modeled simultaneously in several intervals,given the multiplicity and duration of interactions.We considered two approaches for solving the multi-interval equilibrium state problem.The first approach involved directly solving a system of joint optimality conditions for electricity suppliers and consumers.The second approach involved iterative searches until the equilibrium state was reached.This article presents the results of medium-term scheduling using a case study of a simplified real-world power system.

An Efficient Decomposition Method for Bilevel Energy Storage Arbitrage Problem

With the reduction of cost,large-capacity energy storage unit is playing an increasingly important role in modern power systems.When a merchant energy storage unit participates in the power market,its arbitrage problem can be modeled via a bilevel program.The lower-level problem simulates power market clearing and gives the nodal price,based on which the upperlevel problem maximizes the arbitrage profit of energy storage.To solve this bilevel problem,the conventional method replaces the lower level problem with its KKT optimality conditions and further performs linearization.However,because the size of the market clearing problem grows with the scale of the power system and the number of periods,the resulting MILP(mixed-integer linear program)is very challenging to solve.This paper proposes a decomposition method to address the bilevel energy storage arbitrage problem.First,the locational marginal price at the storage connection node is expressed as a piecewise constant function in the storage bidding strategy,so the market clearing problem can be omitted.Then,the storage bidding problem is formulated as a mixed-integer linear program,which contains only a few binary variables.Numeric experiments validate the proposed method is exact and highly efficient.